Using temperature to predict mosquito population dynamics and malaria risk in a changing climate

Background/Question/Methods

Malaria is the most prevalent human vector borne disease in the world, causing significant morbidity and mortality every year. Because the Plasmodium parasites that cause malaria are dependent on Anopheles mosquitoes for transmission, the transmission success of the parasite is tied to the success of the mosquito. Temperature is a critical driver of mosquito population dynamics and it influences life history traits throughout the life span. Additionally, temperature determines the length of time required by Plasmodium parasites to develop to infectiousness inside the mosquito vector. The non-linear nature of the dependence on temperature in both the vector and the parasite makes temperature a complex and important environmental driver in determining the risk for malaria. Here we use a temperature-dependent, stage-structured, delayed differential equation mosquito population model to explore the effects of changing temperatures on mosquito population dynamics and malaria risk. We focus on three locations in Kenya that differ in their ecological, climatic and malarial profiles. We drive our model with location specific temperatures, both historic and projected, from eight downscaled Atmosphere-Ocean General Circulation models.

Results/Conclusions

Running our model with downscaled temperatures provided location specific predictions on the impact that changing temperatures could have on the risk for malaria. We found that the model predicted different abundances of mosquitoes and the potential for malaria risk when comparing historic and future time periods. The model does a good job of matching the predicted historic risk with the observed malaria seasons. Interestingly, the mosquito population as a whole and the subset of the population that has lived long enough to be potential malaria vectors do not necessarily show the same dynamics or seasonality in response to temperature changes. Our results demonstrate a need for a thorough understanding of mosquito biology and for studies that focus on the potential impacts of climate change on disease risk at a localized scale. Additionally, our results point to the importance of understanding the potential shifts in disease risk when planning surveillance and control efforts, both now and in the future.